The rapidly expanding network of roads into the Amazon is permanently altering the world’s largest tropical forest. Most proposed road projects lack rigorous impact assessments or even basic economic justification. This study analyzes the expected environmental, social and economic impacts of 75 road projects, totaling 12 thousand kilometers of planned roads, in the region. We find that all projects, although in different magnitudes, will negatively impact the environment. Forty-five percent will also generate economic losses, even without accounting for social and environmental externalities. Canceling economically unjustified projects would avoid 1.1 million hectares of deforestation and US$ 7.6 billion in wasted funding for development projects. For projects that exceed a basic economic viability threshold, we identify the ones that are comparatively better not only in terms of economic return but also have lower social and environmental impacts. We find that a smaller set of carefully chosen projects could deliver 77% of the economic benefit at 10% of the environmental and social damage, showing that it is possible to have efficient tradeoff decisions informed by legitimately determined national priorities.
Two of the largest protected areas on earth are U.S. National Monuments in the Pacific Ocean. Numerous claims have been made about the impacts of these protected areas on the fishing industry, but there has been no ex post empirical evaluation of their effects. We use administrative data documenting individual fishing events to evaluate the economic impact of the expansion of these two monuments on the Hawaii longline fishing fleet. Surprisingly, catch and catch-per-unit-effort are higher since the expansions began. To disentangle the causal effect of the expansions from confounding factors, we use unaffected control fisheries to perform a difference-in-differences analysis. We find that the monument expansions had little, if any, negative impacts on the fishing industry, corroborating ecological models that have predicted minimal impacts from closing large parts of the Pacific Ocean to fishing.
This paper describes and validates the HydroCalculator Tool developed by Conservation Strategy Fund. The HydroCalculator Tool allows researchers, policy-makers and citizens to easily assess hydropower feasibility, by calculating traditional financial indicators, such as the levelized cost of energy, as well as greenhouse gas emissions and the economic net present value including emissions costs. Currently, people other than project developers have limited or no access to such information, which stifles informed public debate on electric energy options. Within this context, the use of the HydroCalculator Tool may contribute to the debate, by facilitating access to information. To validate the tool’s greenhouse gas calculations, we replicate two peer-reviewed articles that estimate greenhouse gas emissions from different hydropower plants in the Amazon basin. The estimates calculated by the HydroCalculator Tool are similar to the ones found in both peer-reviewed articles. The results show that hydropower plants can lead to greenhouse gas emissions and that, in some cases, these emissions can be larger than those of alternative energy sources producing the same amount of electricity.
This paper uses a property-level dataset of socio-economic and physical information from more than 500 properties in three Andean countries to estimate supply curves of land for conservation via incentive programs. We also evaluate the expected impact of a basic incentive payments program and several proposed improvements in design. We find that the distribution and magnitude of opportunity costs present two challenges. First, a large percentage of the landscape will remain forested in the medium term independent of any incentive. Second, landowners likely place a value on land they plan to clear that significantly exceeds the payment offered by existing incentive programs. We find significant potential to reduce the cost of avoiding deforestation through 1) focusing operations on regions with higher deforestation rates, 2) targeting regions and actors who clear for less profitable activities, and 3) excluding from contracts those areas that are less likely to be cleared.
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